Wasit Journal of Computer and Mathematics Science最新文献_第2页

Real time handwriting recognition system using CNN algorithms 使用CNN算法的实时手写识别系统

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-09-30 DOI: 10.31185/wjcms.157

Maryam Al-Mashhadani

{"title":"Real time handwriting recognition system using CNN algorithms","authors":"Maryam Al-Mashhadani","doi":"10.31185/wjcms.157","DOIUrl":"https://doi.org/10.31185/wjcms.157","url":null,"abstract":"Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition using the recent artificial intelligent algorithms, the conventional neural network (CNN). Different CNN models were tested and modified to produce a system has two important features high performance accuracy and less testing time. These features are the most important factors for real time applications. The experimental results were conducted on a dataset includes over 400,000 handwritten names; the best performance accuracy results were 99.8% for SqueezeNet model.","PeriodicalId":224730,"journal":{"name":"Wasit Journal of Computer and Mathematics Science","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135039691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

From Pixels to Diagnoses: Deep Learning's Impact on Medical Image Processing-A Survey 从像素到诊断:深度学习对医学图像处理的影响——综述

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-09-30 DOI: 10.31185/wjcms.178

Maad Mijwil, None Abdel-Hameed Al-Mistarehi, None Mostafa Abotaleb, None El-Sayed M. El-kenawy, None Abdelhameed Ibrahim, None Abdelaziz A. Abdelhamid, None Marwa M. Eid

{"title":"From Pixels to Diagnoses: Deep Learning's Impact on Medical Image Processing-A Survey","authors":"Maad Mijwil, None Abdel-Hameed Al-Mistarehi, None Mostafa Abotaleb, None El-Sayed M. El-kenawy, None Abdelhameed Ibrahim, None Abdelaziz A. Abdelhamid, None Marwa M. Eid","doi":"10.31185/wjcms.178","DOIUrl":"https://doi.org/10.31185/wjcms.178","url":null,"abstract":"In healthcare, medical image processing is considered one of the most significant procedures used in diagnosing pathological conditions. Magnetic resonance imaging (MRI), computed tomography (CT), ultrasound, and X-ray visualization have been used. Health institutions are seeking to use artificial intelligence techniques to develop medical image processing and reduce the burden on physicians and healthcare workers. Deep learning has occupied an important place in the healthcare field, supporting specialists in analysing and processing medical images. This article will present a comprehensive survey on the significance of deep learning in the areas of segmentation, classification, disease diagnosis, image generation, image transformation, and image enhancement. This survey seeks to provide an overview of the significance of deep learning in the early detection of diseases, studying tumor localization behaviors, predicting malignant diseases, and determining the suitable treatment for a patient. This article concluded that deep learning is of great significance in improving healthcare, enabling healthcare workers to make diagnoses quickly and more accurately, and improving patient outcomes by providing them with appropriate treatment strategies.","PeriodicalId":224730,"journal":{"name":"Wasit Journal of Computer and Mathematics Science","volume":"1598 1-2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136248342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Optimized the Performance of Super Resolution Images by Salt and pepper Noise Removal based on a Modified Trimmed Median Filter 基于改进的裁剪中值滤波器的椒盐噪声去噪优化超分辨率图像的性能

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-09-30 DOI: 10.31185/wjcms.191

None Muthmainnah

引用次数: 1

Modifying the AES Algorithm by Improving the Add Round Key Stage 通过改进Add Round Key Stage修改AES算法

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-09-30 DOI: 10.31185/wjcms.162

Hasan kadhim Ali Alsuwaiedi

{"title":"Modifying the AES Algorithm by Improving the Add Round Key Stage","authors":"Hasan kadhim Ali Alsuwaiedi","doi":"10.31185/wjcms.162","DOIUrl":"https://doi.org/10.31185/wjcms.162","url":null,"abstract":"This study offers a new adjustment to the Advanced Encryption Standard (AES) in order to assure a high degree of security. This is achieved by replacing the binary (XOR) operation with a new (Xo) operation in each add-round-key stage. The Xo operation generated an extra six randomly selected control keys determined by six state tables (2, 4, 6, 8, 10, and 12) produced from the addition operation in the Galois Field GF (2^2 ,2^4 ,2^6 , 2^8, 2^10 and 2^12 ) in order to boost the algorithm's unpredictability. In the suggested method, an adversary requires at least probabilities of keys to break the message; hence, it improves the difficulty of the original AES against brute force attacks. also enhances the performance of additional security metrics, such as NIST tests, compared to the original AES. Consequently, this replacement, including the use of six keys in both the encryption and decryption processes, offers a new level of security and a higher degree of resistance to data breaches. The novelty of the proposed (Xo) technique lies in the construction of GF tables ( 2^6 , 2^10 and 2^12) to be used in the encryption and decryption process for the first time, as well as the approach utilized to create the code for it.","PeriodicalId":224730,"journal":{"name":"Wasit Journal of Computer and Mathematics Science","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135039224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative Analysis of PWM AC Choppers with Different Loads with and Without Neural Network Application 应用与未应用神经网络时不同负载PWM交流斩波器的比较分析

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-09-30 DOI: 10.31185/wjcms.196

None Mariem Bounabi, None Guma Ali

引用次数: 0

Credit Card Fraud Identification using Logistic Regression and Random Forest 基于Logistic回归和随机森林的信用卡欺诈识别

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-09-30 DOI: 10.31185/wjcms.184

Wang Yundong, None Alexander Zhulev, None Omar G. Ahmed

{"title":"Credit Card Fraud Identification using Logistic Regression and Random Forest","authors":"Wang Yundong, None Alexander Zhulev, None Omar G. Ahmed","doi":"10.31185/wjcms.184","DOIUrl":"https://doi.org/10.31185/wjcms.184","url":null,"abstract":"Fraud is an ancient yet ever-changing profession. Because of the digitization of money, financial transactions, banks, fraudsters now have a limitless number of possibilities to perpetrate crime from behind a screen, anywhere around the world. Fraud has a broad influence, with direct ramifications for business and the economy. It is of great worry to cybercrime organizations as recent studies have proven that ML algorithms may successfully be utilized to identify fraudulent transactions in massive amounts of payment data. Such techniques may identify fraudulent transactions in real time, which human auditors may miss. In this research, we apply supervised ML algorithms to the issue of fraud identification by analyzing simulated financial transaction data that is available to the public. Our aim is to show how supervised ML methods may be utilized to successfully identify data with extreme class disproportion. By way of example, we show how exploratory analysis may be utilized to identify fraudulent from real purchases. We also show that Random Forest outperform Logistic Regression when applied to a clearly distinguished dataset.","PeriodicalId":224730,"journal":{"name":"Wasit Journal of Computer and Mathematics Science","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135039169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Novel Particle Swarm Optimization for Channel Allocation in OFDM Based Cognitive Radio Networks 基于OFDM认知无线网络信道分配的粒子群算法

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-09-30 DOI: 10.31185/wjcms.189

Shubham Sharma1

引用次数: 0

Object Detection Techniques: A Review 目标检测技术综述

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-09-30 DOI: 10.31185/wjcms.165

Widad Kadhim, Dr. Mohammed A. Taha

引用次数: 0

Mobile Tourism Recommender System for Users to Get a Better Choice of Tour 手机旅游推荐系统，让用户更好的选择旅游

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-09-30 DOI: 10.31185/wjcms.186

None Mostafa. M.khater

引用次数: 0

Direct Product and Homomorphism of Flower 花的直积与同态

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-07-10 DOI: 10.31185/wjcm.129

Mohd Shahoodh

引用次数: 0